A celebration of the daily triumphs and tribulations of researchers everywhere

scientific discovery

Time management in research can be a bit surreal. Image: Pinterest.com

Time management in research is something of a dark art. The golden rule is to carefully calculate how long it takes to do the various tasks and test the various samples. And then triple it. And add a week.

This generally works well for most projects, but sometimes an experiment reaches a tipping point beyond which the time required to finished the project escalates exponentially. Some liken it to crossing the event horizon of a black hole, beyond which time has no meaning. This is exactly what happened to me this week.

All I really wanted was to test four samples. Four. That’s a small number, it should be easy to get that done. And then I realised I had to include controls because that’s science. The treatments have to be compared to samples without treatments. And compared to a positive control, a treatment that is known to work, just to make sure the method is actually working as it should.

So that’s up to 6 samples. That’s still a small number. No problems.

But then I want to test all these samples in different conditions. After all, just because it works in one, doesn’t mean it works in all of them and vice versa. And then I’ll need controls for each of those different conditions as well.

Now I’m up to about 40 samples. That’s a bigger number but still manageable.

And then I need to consider doing everything in triplicate because that’s also science. Just because it works once, doesn’t mean that it wasn’t a fluke. Or something else happened to the sample so the effect wasn’t actually anything to do with the treatment.

And suddenly there are 120 samples. That is a lot of samples. Now everything takes infinitely more time and I have to factor in little things that are normally taken for granted. Like labelling sample tubes. That’s the morning gone.

And there are just too many samples to comfortably fit into the handy carry containers and too many to run the tests all in one go. The time it takes to do anything has spiralled out to infinity. My quick and easy test has become a major undertaking with exponentially greater complexity and a very distant end point.

My only solace is that at the end of it, when I eventually get there, I know that the results will be real effects and the science behind those results will be sound. That makes for a project that is more likely to pass the peer-review and add to the global understanding of that topic.

Making sense of data can be like trying to find an image in a Magic Eye picture. Image: mentalfloss.com

Research, by nature, is repetitive. The need for demonstrating real effects demands the repeatability and reproducibility of results. This can come at a cost of sanity when initial promising results fail to recur in subsequent samples.

This has been my experience of late when I attempted ‘one last experiment’ before writing a brilliant paper based on an important and surprising finding. That was a couple of months ago. Since then, all my efforts in repeating the experiment have failed to yield good data.

In fact, the only consistent and reproducible trend seems to be the increasing depth of the dint in the wall from where I have been banging my head whilst trying to figure out what’s happening.

So now I’ve taken to desperate measures. I have gone back to the literature to try to explain the phenomenon. Has that helped? Well, no. Not really. It has thrown up many more variables that may influence the results but not offered any solutions. This probably comes back to why I started investigating this topic in the first place.

Then I went on to further desperate measures. I went for a coffee break and then came back to review the data through fresh (-ly caffeinated) eyes. And suddenly, like one of those Magic Eye images, the data resolved itself into a hazy outline of a solution.

I have been studying these samples and this phenomenon for weeks and have accumulated a great deal of data on the topic. Now I know exactly what doesn’t work and, in knowing that, a solution to why it doesn’t work is becoming more obvious.

Maybe soon, with more coffee and squinting, a real solution will present itself and I will get my ground-breaking paper.

Failing that, I should at least be able to produce a strong correlation between the standard errors of averaged replicates and the depth of dints found in walls at head height.

Attending conferences can be hard work but always worth the effort. Image: wallpaper.com

The best perks we get as researchers are not actually pens that are shaped like micropipettes. Nor is it syringe-shaped highlighters, sticky-note paper, or any of the other pretty awesome free stuff that I’ve scored from various lab equipment suppliers over the years. It is the chance to attend international conferences.

This notion was brought to my attention very early in my honours degree. If I do really good work, not only might I save the world and get a Nobel Prize but I would also be PAID to present my work overseas somewhere. And, better than that, people might actually want to hear what I have to say and I could travel around lecturing to various universities.

That was the dream. That dream lead me to a PhD and, eventually, to reality. I am becoming increasingly suspicious that my research may not directly save the world and, unless serendipity steps up sometime, a Nobel Prize may not be heading my way anytime soon. But I might contact the committee again anyway, just in case they lost my number.

One thing reality has shown me is that I do have is the real chance to present at a conference. At this time of year many of us start to peruse the conference alert websites and prepare abstracts for faraway places with relevant topics.

Conferences are where ideas are shared and networks and collaborations are formed. It’s also just cool to get paid to travel regardless of the reams of paperwork that inevitably ensues.

And in meeting other researchers, there is always the possibility that a new idea will spark a stream of thought that leads to a Nobel prize-winning breakthrough, or that a new collaboration will lead to a discovery that will ultimately lead to the world being saved. Hope springs eternal.

At the very least, if all else fails, attending the conference will invariably bring me more lab-supplier-stamped free stuff. And it’s almost worth it just for that.

Science is all about ideas and problem solving and that’s why we love it. But it’s also about lots of hard work to get reproducible results and getting your paper through the potentially gut-wrenching peer-review process.

It’s exhilarating and demoralizing in equal measures although the fewer highs far outweigh the many lows. Some researchers may choose to take everything in their stride but I chose to ride that rollercoaster.

This happened recently for example. I was stuck on a problem that prevented the research from progressing to the next stage. It would be ground-breaking if I could crack this problem and open up a whole new avenue of inquiry. I was motivated.

A great idea did come to me at about 3 o’clock one morning, the Hour of Greatest Wisdom, although the incomprehensible gibberish that I found in my notebook the next morning suggested that this was probably not a real solution.

Then I was explaining my problem to an indulgent non-expert who let me go on and on about the problem. I’m assuming they let me. They didn’t physically stop me from talking so that’s about the same, I’m sure.

In explaining the problem in simple terms, I suddenly had an idea. A clever idea. Genius, in fact. It could even lead to a promotion or, possibly, a Nobel Prize.

But an idea is never enough. It has to be proven to work and the results must be repeatable and reproducible. So I went back to the lab and tried my idea while rehearsing my Nobel Prize acceptance speech.

It seemed to work first time. I had that moment of bated breath that hovers between “Wow, it worked!” and “uh oh, can I do it again?”

I tried again and it still worked. And again. Excitement was building to glorious heights! I told everyone who would listen – or, indeed, who did not walk away quick enough – about this great idea.

Only then did I recheck my calculations. I’d missed a dilution factor, changing the status of my results from “proving I’m clever” to “no significant difference”. I slumped into the low of the “I hate science” mantra and raided the chocolate box before going back to the literature to start again.

After many more attempts, I did solve that problem. Perhaps not at a Nobel Prize level but it did allow us to move on to the next phase of the project. The lows in science can be pretty low but they are always trumped by the exhilaration of new ideas and new discoveries and, because of this, I recommend the rollercoaster ride.

So the story goes, once upon a time Archimedes solved a problem and shouted “Eureka!” condemning researchers ever after to suffer the expectation of doing the same. But this story is really not the best representation of scientific discovery. Flashes of inspiration can contribute to the forward progress but most discoveries result from years or decades of cumulative slog work.

The Eureka! Story is a great story. There’s nudity, a triumphant hero, a greedy villain, and a brilliant catch phrase. Plenty to capture the imagination. But it is so 2000 years ago and people need to stop expecting scientific discoveries to be only the result of one great idea from one person once.

Science is developing at an unprecedented rate thanks to rapid peer-reviewed journal publishing and online access to the whole world of research. It’s an amazing time to be in science.

Teams of people across the globe are working together to solve problems, tiny increment by tiny increment. This involves very different people joining together, overcoming language barriers and cultural differences to reach a common goal. And that’s just across scientific disciplines. There’s no App available yet for converting chemistry jargon to biology jargon.

Science is brilliant story of unlikely heroes banding together for the greater good, almost like highly trained warriors from different armies who suddenly have to unite against a new and monstrous enemy.

This is even better than Archimedes’ Eureka story on so many levels. All we really need to capture people’s imagination now is a bloody good catch phrase.